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existing quantitative methods in international nuclear safeguards with state-of-the-art artificial intelligence/machine learning (AI/ML) algorithms Contribute to standardising methodologies for calculating
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to develop a 3D-generative algorithm for pharmaceutical drug design by using or combining novel machine learning approaches? How would you integrate machine learning, physics-based methods in an early-stage
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research studies for automated image analysis. In particular, you will: Plan, develop, and implement AI/ML algorithms for pathology image analysis. Integrate multi-modal data (e.g., genomics, clinical data
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. At W7‑X, a pellet injector is available to investigate the pellet injection and subsequent particle distribution within a fusion relevant plasma. The observation of pellet ablation and plasma transport
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, and characterization Develop gate implementations, benchmarking and algorithms Work on the interdisciplinary challenges in systems engineering Install and improve experimental setups and fabrication
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energy use more efficient. We develop new optimization methods, machine learning algorithms, and prototypical systems controlling complex energy systems like electric grids and thermal systems for a
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unique three-dimensional maps of neurotransmitter receptor distributions in the human, non-human primate and rodent brain Develop efficient processing pipelines enabling the spatial integration
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IMWS. This opens up new perspectives in electron energy loss spectroscopy (XEELS), enabling - among other things - the determination of pair distribution functions (based on EXELFS) with nanometer
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the vertical flux of organic matter in different oceanic regions. This will include the use of in situ camera systems, sediment traps, and bio-optical platforms to quantify particle abundance, size distribution
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/distributed programming and/or solid UNIX skills Practical experience with ML/DL workflows and common software libraries Your experience should be documented in research papers and Open Source code projects